library(CoxBoost)
n <- 400; p <- 1000
set.seed(129)
group<-rbinom(n,1,0.5)
x <- matrix(rnorm(n*p,0,1),n,p)
beta.vec1  <- c(c(1,1,1,1,1),rep(0,p-5))  
beta.vec0  <- c(c(0,0,0,0,0),rep(0,p-5)) 
linpred<-ifelse(group==1,x %*% beta.vec1,x %*% beta.vec0)
set.seed(1234)
real.time<- (-(log(runif(n)))/(1/20*exp(linpred)))
cens.time <- rexp(n,rate=1/20)
obs.status <- ifelse(real.time <= cens.time,1,0)
obs.time <- ifelse(real.time <= cens.time,real.time,cens.time)

RIF <- resample.CoxBoost(time=obs.time,status=obs.status,x=x,rep=100, maxstepno=200,multicore=FALSE,
                         mix.list=c(0.001, 0.01, 0.05, 0.1, 0.25, 0.35, 0.5, 0.7, 0.9, 0.99), 
                         stratum=group,stratnotinfocus=0,penalty=sum(obs.status)*(1/0.02-1),
                         criterion="hscore",unpen.index=NULL) 

stabtrajec(RIF)
weightfreqmap(RIF)